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Fix potential uninitialized in Symmetric building of NormalChol cache #453

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Dec 26, 2023
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Fix potential uninitialized in Symmetric building of NormalChol cache #453

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2 changes: 1 addition & 1 deletion src/factorization.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -1010,7 +1010,7 @@ function init_cacheval(alg::NormalCholeskyFactorization, A, b, u, Pl, Pr,
maxiters::Int, abstol, reltol, verbose::Bool,
assumptions::OperatorAssumptions)
A_ = convert(AbstractMatrix, A)
return ArrayInterface.cholesky_instance(Symmetric((A)' * A), alg.pivot)
return ArrayInterface.cholesky_instance(Symmetric(Matrix{eltype(A)}(undef,0,0)), alg.pivot)
end

function init_cacheval(alg::NormalCholeskyFactorization,
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41 changes: 21 additions & 20 deletions test/default_algs.jl
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Expand Up @@ -45,24 +45,25 @@ solve(prob)
prob = LinearProblem(sprand(11000, 11000, 0.5), zeros(11000))
solve(prob)

@static if VERSION >= v"v1.9-"
# Test inference
A = rand(4, 4)
b = rand(4)
prob = LinearProblem(A, b)
VERSION ≥ v"1.10-" && JET.@test_opt init(prob, nothing)
JET.@test_opt solve(prob, LUFactorization())
JET.@test_opt solve(prob, GenericLUFactorization())
@test_skip JET.@test_opt solve(prob, QRFactorization())
JET.@test_opt solve(prob, DiagonalFactorization())
#JET.@test_opt solve(prob, SVDFactorization())
#JET.@test_opt solve(prob, KrylovJL_GMRES())
# Test inference
A = rand(4, 4)
b = rand(4)
prob = LinearProblem(A, b)
VERSION ≥ v"1.10-" && JET.@test_opt init(prob, nothing)
JET.@test_opt solve(prob, LUFactorization())
JET.@test_opt solve(prob, GenericLUFactorization())
@test_skip JET.@test_opt solve(prob, QRFactorization())
JET.@test_opt solve(prob, DiagonalFactorization())
#JET.@test_opt solve(prob, SVDFactorization())
#JET.@test_opt solve(prob, KrylovJL_GMRES())

prob = LinearProblem(sparse(A), b)
#JET.@test_opt solve(prob, UMFPACKFactorization())
#JET.@test_opt solve(prob, KLUFactorization())
#JET.@test_opt solve(prob, SparspakFactorization())
#JET.@test_opt solve(prob)
@inferred solve(prob)
@inferred init(prob, nothing)
end
prob = LinearProblem(sparse(A), b)
#JET.@test_opt solve(prob, UMFPACKFactorization())
#JET.@test_opt solve(prob, KLUFactorization())
#JET.@test_opt solve(prob, SparspakFactorization())
#JET.@test_opt solve(prob)
@inferred solve(prob)
@inferred init(prob, nothing)

prob = LinearProblem(big.(rand(10, 10)), big.(zeros(10)))
solve(prob)
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